5 papers · 1 filter
From Semantic To Instance: A Semi-Self-Supervised Learning Approach
Keyhan Najafian, Farhad Maleki, Lingling Jin +1
Instance segmentation is essential for applications such as automated monitoring of plant health, growth, and yield. However, extensive effort is required to create large-scale dat…
SynthSet: Generative Diffusion Model for Semantic Segmentation in Precision Agriculture
Andrew Heschl, Mauricio Murillo, Keyhan Najafian +1
This paper introduces a methodology for generating synthetic annotated data to address data scarcity in semantic segmentation tasks within the precision agriculture domain. Utilizi…
A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation
Keyhan Najafian, Farhad Maleki, Lingling Jin +1
Video object segmentation (VOS) -- predicting pixel-level regions for objects within each frame of a video -- is particularly challenging in agricultural scenarios, where videos of…
Semi-Self-Supervised Domain Adaptation: Developing Deep Learning Models with Limited Annotated Data for Wheat Head Segmentation
Alireza Ghanbari, Gholamhassan Shirdel, Farhad Maleki
Precision agriculture involves the application of advanced technologies to improve agricultural productivity, efficiency, and profitability while minimizing waste and environmental…
Modified CycleGAN for the synthesization of samples for wheat head segmentation
Jaden Myers, Keyhan Najafian, Farhad Maleki +1
Deep learning models have been used for a variety of image processing tasks. However, most of these models are developed through supervised learning approaches, which rely heavily…